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Conference Partners

The rise of ‘Big Data’ has been characterized by a rapidly increasing availability and diversity of data that will play a role in shaping the future of Geoscience Research and the Hydrocarbon Industry. The Geoscience community has been slow to embrace the Big Data technologies that are revolutionizing other sciences such as the pharmaceutical industry and medical research. Where advances in data acquisition and interpretation technologies are being made in academic Geoscience, progress in uptake has been hampered by unstructured data, stored in silos.

This three day meeting brought together early career geoscientists with leading industry and academic experts to discuss the opportunities and challenges of Big Data and showcase advances in data collection and interpretation technology. It presented an opportunity to learn and collaborate between Geoscience and Computer Science on the subject of Big Data. This was an excellent forum for networking and an opportunity for graduate students and young professionals to present their research. The conference offered more experienced hydrocarbon geoscientists new research, ideas and concepts and the chance to add their experience to a panel discussion.

The programme included virtual fieldtrips and software demonstrations of technology advances in Big Data on a variety of scales, from regional subsurface interpretation, to virtual fieldtrips and virtual outcrops, with special sessions on automated interpretation and artificial intelligence.

A panel discussion on ‘The Future of Big Data’ was held at the close of the second day.

Keynote Speakers

Liz Wild (Shell)

Dr Satyam Priyadarshy (Halliburton)

Nick Richardson (OGA)

Ed Parsons (Google)

Garry Baker (BGS Group)

Steve Garrett (Chevron)

John Thurmond (Statoil)

Eirik Larsen/Chris Jackson (Earth Science Analytics)

John Howell (University of Aberdeen)

A full programme can be downloaded from the 'Downloads' box on the right.

Python and AI basics coding workshop for Geoscientists

The objective of this short course was to demonstrate the flexibility and ease of coding in Python and AI ,coupled to the industry standard RokDoc GeoPrediction software, enabling the user to implement their own desired algorithms in Python. We started by teaching some basic well log operations using Python and the external interface to RokDoc. Then we extended this application to basic machine learning algorithms for facies classification using freely available Python libraries. The course was for entry level practitioners and involves hands on coding experiments, hence having some Python skills is an advantage but not essential. We were aiming for early stage professional Geoscientists and Engineers in line with conference objectives.

The instructors were Russell Taylor and Dr Ehsan Naeini of Ikon Science.